Tools + TOFU

How does an AI API tester speed up integration?

An AI API tester sends a real request from the browser: choose an endpoint and model, write system and user messages, set temperature and max tokens, and inspect the raw response. A good tester also exercises streaming, JSON mode and function calling, then generates ready-to-run cURL, Python and JavaScript snippets so the working call becomes your first integration.

Key facts

Tool typeFree OpenAI-compatible request builder and snippet generator
EndpointsChat completions with streaming, JSON mode and function calling
Models30+ models selectable from the live catalogue
AuthAPI key generated in the dashboard; free plan needs no card
Snippet outputcURL, Python and JavaScript examples for each test call
Response inspectionRaw JSON, token usage, finish reason and latency
Free plan2 free AI models (plugsky-micro, plugsky-lite), no card required
Product statusLive

TL;DR

  • Test the exact call in the browser before writing application code.
  • Exercise streaming, JSON mode and function calling, not just plain chat.
  • Copy the generated snippet and keep the tested parameters verbatim.
  • Check finish reason and token usage to catch truncation early.
  • One OpenAI-compatible endpoint covers 30+ models, so the same snippet works across tiers.

How it works, step by step

  1. Create an API key in the Plugsky dashboard; the free plan includes 2 free models and no card.
  2. Open the OpenAI-compatible API tester and point it at https://api.plugsky.com/v1.
  3. Pick a model from the catalogue and write your system and user messages.
  4. Set temperature, max tokens and any response-format or tool definitions you need.
  5. Send the request and inspect the raw JSON, token usage and finish reason.
  6. Repeat with streaming enabled, then with a tool call, to confirm your parser handles both shapes.
  7. Copy the generated cURL, Python or JavaScript snippet into your codebase and run your tests.
1Create an API keyin the Plugskydashboard; the free2Open theOpenAI-compatibleAPI tester and3Pick a model fromthe catalogue andwrite your system4Set temperature,max tokens and anyresponse-format or5Send the requestand inspect the rawJSON, token usage6Repeat withstreaming enabled,then with a tool

Try it yourself

Open the OpenAI-compatible API tester →

What to test beyond a basic chat call

A basic completion proves the key works; it does not prove your integration. Streaming changes how bytes arrive and how you render them, so test partial chunks and the final usage block. JSON mode should be exercised with your real schema, not a toy example, because models fail differently on nested and optional fields. Function calling needs at least one multi-turn tool loop: model requests a tool, your code returns a result, the model continues. If those three paths work, most production surprises are already covered.

Reading the response like an engineer

Inspect the fields your app will actually consume. finish_reason tells you whether the model stopped or hit the token ceiling, which is the most common cause of mysteriously empty output. The usage block separates prompt and completion tokens and feeds directly into the token calculator. Error shapes matter too: a 401, a 429 and a malformed-tool-arguments error should each map to a different branch in your retry logic, so trigger them deliberately while you are still in the browser.

From tested call to shipped code

The generated snippet is a starting point, not a substitute for structure. Move the base URL and model name into configuration, wrap the client so you can swap providers, and keep timeouts and one retry with jitter. Because the endpoint is OpenAI-compatible, the snippet also works with the official SDKs by changing base_url and the model name. Run the same snippet against two model tiers — a small free model and a frontier model — to see the quality and latency difference on your own prompt before committing to a default.

Honest comparison

CapabilityPlugsky testerTypical playgroundThrowaway script
Streaming testYes, with raw chunk inspectionSometimesYou implement it
JSON mode testYes, with your schemaRarelyManual
Function calling testYes, multi-turn tool loopRarelyManual
Snippet generationcURL, Python, JavaScriptVariesYou write it
Model coverage30+ models, one endpointVendor models onlyWhatever you wire up
Usage visibilityToken usage and finish reason in the responsePartialYou log it

Frequently asked questions

Is the API tester free?

Yes. The tester is a free browser tool; model calls consume your plan's usage, and the free plan includes 2 free models with no card.

Which endpoint does it call?

It targets the OpenAI-compatible chat completions endpoint at https://api.plugsky.com/v1, so anything you verify there works with the official OpenAI SDKs.

Can I test streaming?

Yes. Enable streaming in the tester to see chunks arrive and confirm your client renders partial output correctly.

Does it support function calling?

Yes. Define tools with JSON Schema, send a prompt, and inspect the tool call and the follow-up turn.

Are my API keys stored?

Treat the tester like any API client: use keys you can rotate and never paste production secrets into shared environments.

Can I compare models on the same prompt?

Yes. Keep the prompt fixed, change the model, and compare output, token usage and latency before choosing a default.

What snippet languages are generated?

cURL, Python and JavaScript, covering the call you just tested with the same parameters.

Is the tester the same as the migration checker?

No. The tester verifies individual calls; the migration checker audits a whole codebase for OpenAI compatibility.